A Reliable and Reconfigurable Robot Learning Framework for Accelerating Materials Discovery (R3L4AMD)

The future of chemical discovery, for example using genAI to identify novel molecules and materials with tailored functions, will rely on the data generated from physical experiments. Current robotic and automation approaches are not up to this challenge, lacking generalisation and scalability. Today, it takes years to build robotic workflows [1, 2, 3]; the main bottleneck is the manual system design, production, testing, adaptation and iteration required to attain safe, reliable performance. In this project, we will rethink how 'robotic chemists' are deployed using 'A Reliable and Reconfigurable Robot Learning Framework for Accelerating Materials Discovery' (R3L4AMD). We will accelerate the design automated workflows by transitioning from manual, task-specific robot programming to a simulation-to-reality paradigm with embedded formal methods that rigorously specify experimental goals and safety constraints. We will develop ‘robotic chemists’ using a physics-based robot chemistry simulation framework, which will automate the production of robot policies with provable performance and safety guarantees. We will deploy and validate this approach on a real robot setup in an autonomous materials discovery lab. 

Specifically, the student will:

• Develop a novel framework for end-to-end autonomous robotic chemists with performance and safety guarantees using a simulation-to-reality framework ;
• Deploy and validate the system in real-world materials discovery experiments;
• Contribute to the ongoing research efforts at the UoL related to AI-driven robotic scientists;
• Collaborate with external partners in our collaborative network of ongoing multidisciplinary projects.

This project will be supervised by Dr Gabriella Pizzuto, Prof Andy Cooper and Dr Shufang Zhu. Any informal enquiries about the project can be directed to Gabriella.Pizzuto@liverpool.ac.uk.

The global need for researchers with capabilities in materials chemistry, digital intelligence and automation is intensifying because of the growing challenge posed by Net Zero and the need for high-performance materials across multiple sectors. The disruptive nature of recent advances in artificial intelligence (AI), robotics, and emerging quantum computing offers timely and exciting opportunities for PhD graduates with these skills to make a transformative impact on both R&D and society more broadly.

The University of Liverpool EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry is therefore offering multiple studentships for students from backgrounds spanning the physical and computer sciences to start in October 2025. These students will develop core expertise in robotic, digital, chemical and physical thinking, which they will apply in their domain-specific research in materials design, discovery and processing. By working with each other and benefiting from a tailored training programme they will become both leaders and fully participating team players, aware of the best practices in inclusive and diverse R&D environments.

This training is based on our decade-long development of shared language and student supervision between the physical, engineering and computer sciences, and takes place in the Materials Innovation Factory (MIF), the largest industry-academia colocation in UK physical science. The training content has been co-developed with 35 industrial partners and is designed to generate flexible, employable, enterprising researchers who can communicate across domains.

Applicant Eligibility

Candidates will have, or be due to obtain, a Master’s Degree or equivalent related to Physical Science, Engineering or Computational Science. Exceptional candidates with a First Class Bachelor’s Degree in an appropriate field will also be considered.

Application Process

Applicants are advised to apply as soon as possible no later than 17^th February 2025. The CDT will hold two rounds of applications assessment:

·      Assessment Round 1: for all applications received between 11^th December 2024 – 15^th January 2025.

·      Assessment Round 2: for all applications received between 16^th January 2025 – 17^th February 2025

Applicants who wish to be considered in Assessment Round 1 must apply by 15^th January 2025. Projects will be closed when suitable candidate has been identified (this could be before the 17th February 2025 deadline).

Please review our guide on “How to Apply” carefully and complete the online postgraduate research application form to apply for this PhD project in Computer Science.

We strongly encourage candidates to get in touch with the supervisory team to get a better idea of the project.

We want all our Staff and Students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We are committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances. For example, if you have a disability you may be entitled to a Disabled Students Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result.